Evaluating and Optimizing Opportunity Fast-Charging Schedules in Transit Battery Electric Bus Networks

Abdelwahed A, Berg PL, Brandt T, Collins J, Ketter W


Abstract
Public transport operators (PTOs) increasingly face a challenging problem in switching from conventional diesel to more sustainable battery electric buses (BEBs). In this study, we optimize the opportunity fast-charging schedule of transit BEB networks in order to minimize the charging costs and the impact on the grid. Two mixed-integer linear programming (MILP) formulations that use different discretization approaches are developed and compared. Discrete-Time Optimization (DTO) resembles a time-expanded network that discretizes the time and decisions to equal discrete slots. Discrete-Event Optimization (DEO) discretizes the time and decisions into nonuniform slots based on arrival and departure events in the network. In addition to the DEO’s higher practicability, the comparative computational study carried out on the transit-bus network in the city of Rotterdam, Netherlands, shows that the DEO is superior to the DTO in terms of computational performance. To show the potential benefits of the optimal schedule, it is compared with two reference common-sense greedy strategies: First-in-First-Served and Lowest-Charge-Highest-Priority.



Publication type
Forschungsartikel (Zeitschrift)

Peer reviewed
Yes

Publication status
Published

Year
2020

Journal
Transportation Science

Volume
54

Issue
6

Pages range
1601-1615

Language
English

ISSN
0041-1655

DOI

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